get_server_info
Discover server capabilities, available tools, supported file formats, and resource limits to plan workflows with DataBeak's CSV data processing tools.
Instructions
Get DataBeak server capabilities and supported operations.
Returns server version, available tools, supported file formats, and resource limits. Use to discover what operations are available before planning workflows.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Implementation Reference
- The primary handler function implementing the get_server_info tool. It retrieves server settings and constructs a detailed ServerInfoResult with capabilities categorized by data I/O, manipulation, analysis, validation, session management, and null handling.async def get_server_info( ctx: Annotated[Context, Field(description="FastMCP context for progress reporting")], ) -> ServerInfoResult: """Get DataBeak server capabilities and supported operations. Returns server version, available tools, supported file formats, and resource limits. Use to discover what operations are available before planning workflows. """ await ctx.info("Retrieving DataBeak server information") # Get current configuration settings settings = get_settings() server_info = ServerInfoResult( name="DataBeak", version=__version__, description="A comprehensive MCP server for CSV file operations and data analysis", capabilities={ "data_io": [ "load_csv_from_url", "load_csv_from_content", ], "data_manipulation": [ "filter_rows", "sort_data", "select_columns", "rename_columns", "add_column", "remove_columns", "change_column_type", "fill_missing_values", "remove_duplicates", "null_value_support", # Explicitly mention null support ], "data_analysis": [ "get_statistics", "correlation_matrix", "group_by_aggregate", "value_counts", "detect_outliers", "profile_data", ], "data_validation": [ "validate_schema", "check_data_quality", "find_anomalies", ], "session_management": [ "multi_session_support", "session_isolation", "auto_cleanup", ], "null_handling": [ "json_null_support", "python_none_support", "pandas_nan_compatibility", "null_value_insertion", "null_value_updates", ], }, max_download_size_mb=settings.max_download_size_mb, session_timeout_minutes=settings.session_timeout // 60, ) await ctx.info("Server information retrieved successfully") return server_info
- Pydantic model defining the structured output schema for the get_server_info tool response, including server metadata and capabilities.class ServerInfoResult(BaseToolResponse): """Response model for server information and capabilities.""" name: str = Field(description="Server name and identification") version: str = Field(description="Current server version") description: str = Field(description="Server description and purpose") capabilities: dict[str, list[str]] = Field( description="Available operations organized by category", ) max_download_size_mb: int = Field(description="Maximum download size from URLs in MB") session_timeout_minutes: int = Field(description="Default session timeout in minutes")
- src/databeak/servers/system_server.py:270-270 (registration)Registration of the get_server_info handler as an MCP tool on the system_server FastMCP instance with explicit name.system_server.tool(name="get_server_info")(get_server_info)